OBJECTIVES: To find out the prevalence, origin and cost associated with Induced Prescription (IP) in Primary Health Care (PHC) in the West of Gipuzkoa (WG). To find out the extent to which PHC doctors agree with IP. To analyse the adaptation of IP to PHC clinical management contract indicators. MATERIALS AND METHODS: Design descriptive multi-centre cross-study. LOCATION: Primary Health Care, 38 doctors from 17 WG PHC units. PARTICIPANTS: Pharmaceutical prescriptions eligible for finance over a period of two days in outpatients and chronic diseases generated by the Osabide computer application. Variables analysed: type of prescription, origin, prescriber, diagnosis, price and level of agreement. RESULTS: A total of 6.919 prescriptions were made out, with 44% (95% CI: 42.8-45.1) being IP. Of the total cost, 62.2% was put down to IP, with an average price per prescription of €22.3,and in non-induced prescription (NIP) it was €10.62. The therapeutic subgroups with the highest cost were lipid lowering and bronchodilator drugs. The level of disagreement of the doctors taking part in IP was 28.8%. The adaptation to the quality indicators of the prescription was higher in NIP than in IP. CONCLUSIONS: There is a high percentage of IP associated with high costs attributed to PHC. The percentage of disagreement in PHC with regard to IP is significant. There is a high influence of IP on the evaluation of the quality indicators established in PHC.
OBJECTIVES: To find out the prevalence, origin and cost associated with Induced Prescription (IP) in Primary Health Care (PHC) in the West of Gipuzkoa (WG). To find out the extent to which PHC doctors agree with IP. To analyse the adaptation of IP to PHC clinical management contract indicators. MATERIALS AND METHODS: Design descriptive multi-centre cross-study. LOCATION: Primary Health Care, 38 doctors from 17 WG PHC units. PARTICIPANTS: Pharmaceutical prescriptions eligible for finance over a period of two days in outpatients and chronic diseases generated by the Osabide computer application. Variables analysed: type of prescription, origin, prescriber, diagnosis, price and level of agreement. RESULTS: A total of 6.919 prescriptions were made out, with 44% (95% CI: 42.8-45.1) being IP. Of the total cost, 62.2% was put down to IP, with an average price per prescription of €22.3,and in non-induced prescription (NIP) it was €10.62. The therapeutic subgroups with the highest cost were lipid lowering and bronchodilator drugs. The level of disagreement of the doctors taking part in IP was 28.8%. The adaptation to the quality indicators of the prescription was higher in NIP than in IP. CONCLUSIONS: There is a high percentage of IP associated with high costs attributed to PHC. The percentage of disagreement in PHC with regard to IP is significant. There is a high influence of IP on the evaluation of the quality indicators established in PHC.
Authors: Amaia Calderón-Larrañaga; Beatriz Poblador-Plou; Francisca González-Rubio; Luis Andrés Gimeno-Feliu; José María Abad-Díez; Alexandra Prados-Torres Journal: Br J Gen Pract Date: 2012-12 Impact factor: 5.386
Authors: Arritxu Etxeberria; Idoia Alcorta; Itziar Pérez; Jose Ignacio Emparanza; Elena Ruiz de Velasco; Maria Teresa Iglesias; Rafael Rotaeche Journal: BMC Health Serv Res Date: 2018-02-08 Impact factor: 2.655
Authors: Amaia Calderón-Larrañaga; Luis A Gimeno-Feliu; Francisca González-Rubio; Beatriz Poblador-Plou; María Lairla-San José; José M Abad-Díez; Antonio Poncel-Falcó; Alexandra Prados-Torres Journal: PLoS One Date: 2013-12-20 Impact factor: 3.240